{"id":"W4385319915","doi":"10.2196/49452","title":"Fact-Checking Cancer Information on Social Media in Japan: Retrospective Study Using Twitter","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Misinformation; Social media; Cancer; Medicine; Internet privacy; Computer science; World Wide Web; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001585644,0.0003965748,0.0007988719,0.002863611,0.001575062,0.001583875,0.0005613166,0.0006507253,0.001992623],"category_scores_gemma":[0.008386811,0.0007073989,0.000823048,0.00532903,0.0005269746,0.002255572,0.001505837,0.0006972788,0.0006180715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001137762,"about_ca_system_score_gemma":0.00142133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0185627,"about_ca_topic_score_gemma":0.02069731,"domain_scores_codex":[0.9978409,0.0003929415,0.0006799405,0.00039237,0.000421248,0.0002726115],"domain_scores_gemma":[0.9926461,0.001323494,0.00324933,0.000602191,0.001589488,0.0005894855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000899824,0.00004881097,0.9925526,0.0002675387,0.00006152715,0.0003604639,0.002602966,0.00001320835,0.0001368614,0.00003459417,0.0009376842,0.002893814],"study_design_scores_gemma":[0.00001314996,0.00007690694,0.9869033,0.000193208,0.0002283786,0.0007183503,0.007813862,0.0002712722,0.0001658731,0.00004943387,0.003530104,0.00003610931],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928715,0.001300005,0.0002610908,0.0002713923,0.00003748234,0.0002000795,0.003663394,0.00001372607,0.00138143],"genre_scores_gemma":[0.9930037,0.001607744,0.0004219385,0.0003382152,0.00006858644,0.0003606788,0.003492738,0.0000224418,0.0006841423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0185627,"threshold_uncertainty_score":0.03690934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4536190924751264,"score_gpt":0.5887518360497,"score_spread":0.1351327435745737,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}